Recent Trends in Intelligent Job Shop Scheduling

Abstract

Job-shop scheduling (JSS) belongs to the large class of NP-complete (nondeterministic polynomial time complete) problems, just as the travelling salesperson problem (TSP). The complexity of job-shop scheduling characterizes many real-life situations such as the scheduling of classes of classrooms, airplane flights, courses to professors, hospital patients to beds, and so forth. In this paper, we shall give all related definitions to this problem formulation. More over we will give an idea regarding the techniques used for solving the job shop scheduling problem. Among these methods we find classical methods and more advanced ones such as artificial intelligence (AI). Recent developments in artificial intelligence (AI) have led to the use of knowledge-based techniques for solving scheduling problems. We survey several existing intelligent planning and scheduling systems with the aim of providing a guide to the main AI techniques used. We survey some of the more successful planning and scheduling systems, and highlight their features. A comprehensive list of references related to the subject is provided in the end of this paper